1. Field
Embodiments described herein generally refer to activation systems that are triggered based on received speech signals.
2. Background
Speech recognition systems often include a speech recognition engine that compares portions of a received signal to stored information to determine what a user has said to a device. Some of these speech recognition systems are designed to be able to respond to speech from a user at any time. Consequently, the speech recognition engine must remain active constantly so that it can monitor the ambient environment for speech.
Because speech is often not received for most of the time that the speech recognition engine is running, the speech recognition engine wastes power monitoring the ambient environment. Especially in wireless and mobile devices that are often battery-powered, this waste of power can be a substantial concern for system designers.
Some speech recognition engines save power by operating as multi-state devices. In a low power state, the speech recognition engine only uses enough power to detect certain specific words that have been previously designated as triggers. Once one of these words is detected, the speech recognition engine transitions to a fully-operational state in which it can recognize a full vocabulary of words. Although multi-state implementations provide some power savings, these savings are often modest because many of the components needed to recognize the full vocabulary of words are also needed to detect the specific words designated as triggers. Therefore, these components must remain active even in the low power state.